Most approaches to animation of autonomous computer generated characters do not utilise a character's view of its environment. Input for a character's artificial intelligence is typically obtained by searching a scene description database for input data and performing involved calculations to obtain required input data. This data is supplied to the character's artificial intelligence engine which outputs character behaviour information.
This approach has a number of disadvantages as follows:                1. occlusion must be ignored or else computed at a high computational cost.        2. resolution of input data is not proportional to distance unless this feature is explicitly computed.        3. visibility due to field of view has to be explicitly computed.        4. topological features such as holes, concavities and profile are difficult and inefficient to represent in a non vision based system.        5. Spatial subdivision optimisation must be used to avoid n squared performance scalability.        6. To provide accurate input information is computationally expensive and limits the number of autonomous computer generated characters that can be simultaneously controlled.        
Reynolds, “Flocks, Herds, and Schools: A Distributed Behavioral Model” Computer Graphics, 21(4), July 1987, pp. 25-34, teaches automated behaviour of characters in a 3-D environment where the characters have limited knowledge of their environment.
Systems whereby the limited knowledge available to the character is derived from an image from the perspective of the character are also known.
However, such known systems do not compute distortion free images for wide angles of view.
A disadvantage of such known systems is characters are unable to be realistically responsive to their entire environment represented as a spherical view from the character's position.
Furthermore, the known systems process the image analytically to identify characteristics about objects within the field of view.
A disadvantage of such systems is that this processing costs computation time.
Another disadvantage of such systems is that the data loses generality and thereby limits the flexibility of the use of the data by the engine which determines behaviour of the character.
Another disadvantage is that analytical solutions are often susceptible to unpredictable or unstable behaviour when the input data is not as expected.